The implementation of the UN Madrid International Plan of Action on Ageing directives in Australia
Bibliographic record
Abstract
Government budgets are an important indicator of governments’ priorities in shaping public policy. Budgetary allocations will be evaluated within the policy framework developed in the “National Strategy for an Ageing Australia” to determine whether the rights of older persons as espoused by the United Nations “Principles for Older Persons” and by the Madrid International Plan of Action on Ageing are being observed by governments in Australia. The budgets issued by the Australian Federal, Victorian State and two Victorian local governments were examined and analysed using content analysis, commencing from the introduction of the National Strategy in 2001 till 2011. Eight policy areas were identified in the National Strategy around the theme - “health promotion and well-being throughout life”. The Federal Government provided support that directly benefited older persons such as health assessments for older Australians for five out of the eight policy areas. However, throughout the analysed period, the level of budgetary support for these areas was either reduced or discontinued, with many policy areas being only supported for short periods of time. Other government bodies did not provide any funding, except for one initiative introduced in the 2001/02 Victorian State budget. Regarding support for initiatives benefiting the broader community, such as cancer awareness campaigns, out of the eight policy areas identified, four were supported by the Federal Government, three by the Victorian and one by the Whitehorse Council. The evidence shows that healthy ageing can significantly offset the negative effects of ageing on a society. The results of this study revealed that Australian governments provide only limited support of health promotion and well-being in their budgetary allocations. To succeed in preparing the Australian society for an ageing population, more proactive actions are required on the part of Australian governments at all levels.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.017 | 0.035 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".